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\title{Synopsis of presentations at the \\$2^{nd}$ Annual BIG DATA WORLDSHOW/MALAYSIA 9-10 SEP 2014}
\author{Winn Voravuthikunchai}

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\section{Case study in Banking and Finance.
The Real-World Use of Big Data in Financial Services.}
Loon Wing Yuen:
Director, Innovation
Group Information Services, Group Information and Operations Division, CIMB
\subsection{Synopsis}
CIMB is investigating the potential to used their data, collected from OctoPay (Facebook Banking) and many Facebook-related marketing campaigns, in order to leverage their debit card 
revenue. 

Since the Debit Card business is new, they have limited transactional volumes which is insufficient 
to generate good insights for the business. To solve the problem, they have been searching for correlation between Facebook likes and merchant spend. 
Assuming if there is a good correlation, they could then take a wider range of merchant categories in Facebook likes, and use them 
for marketing campaign interventions. At this stage, they have discovered good correlations among certain merchant categories and brands. 
Their facing main challenges includes, (i) significant amount of data cleansing and transformations required, and (ii)
not every Facebook like is correlated to the merchant spend.

\subsection{Relevant}
Extracting information from social media is in our interest, and has to be done in the near future. AirAsia has 
twelve Facebook fan pages, eight Twitter accounts, four Instagrams accounts, three Youtube accounts, 
three LINE official accounts. Huge volume of data can be harvested from these social media channels. Once we obtain the data, 
we could build predictive models, and different types of analysis such as sentiment analysis that can benefit different 
departments in our organization.  

\section{Big Data in Metallurgy: New Approach to Process Optimization.}

Damir Gaynanov: Data Scientist, Head of Department, Ural Federal University 

\subsection{Synopsis}
This presentation gave a successful story of using Big Data technologies for optimizing the work flow of production lines in metallurgy plant. 

In a metallurgy plant, hundreds of machine units are involved, operating by different departments. 
The main bottleneck of the production is the lack of efficient communications and optimizations, resulting in a large number of pending processes which need to wait for 
other units to transmit inputs. They showed that using big data technology, the 
economic benefits for one process flow during 1 year reached 6 million USD, while  
the costs of implementation of EXPERT BASE system based on BIG DATA technology is 4 million USD.
Technical requirements include data warehousing (Teradata Active IDW), data discovery (Teradata Aster), and data platform (Hadoop).
\subsection{Related}
Expert based system, could be used for automating complex decision making tasks, such as how route analysis adjust prices. 
In artificial intelligence, an expert system is a computer system that emulates the decision-making ability of a human expert. 
Expert systems are designed to solve complex problems by reasoning about knowledge, represented primarily as if–then rules.




\section{Improving Information Security with Big Data}
Thillai Raj T. Ramanathan: Chief Technology Officer, MIMOS BERHAD
\subsection{Synopsis}
The speaker addressed the question of can security be improved as more knowledge is derived from larger pools of information through IT. 
Several demos from projects developed for the government in the domain of security has been shown. 
For example, crime detection system, based on computer vision, uses historical data from CCTV to train classification models to alert 
police officers when a crime is likely to be occurring. Another example, is to detect unattended luggage at airports.
\subsection{Relevant}
Computer vision and image processing can be used for various application in airline business such as 
passenger sentiment analysis, person identification, suspect detection. 



\section{Customer Experience Management: How Big Data can Enhance Customer Experience}
Jonathan Lim: General Manager – Group Information Technology, Sunway Berhad 
\subsection{Synopsis}
Typically, there is a big gap between organizations and customers since their focus is different. For example, organizations think about how 
to increase sales, while customers think about how to reduce their spend. Big data can help organizations to reduce the gap by 
engaging with their customers via multiple communication channels, 
having interactions in order to understand the need of the customers. 

\subsection{Relevant}
Two-way communications using social media, mobile application, advertising and promotion, is useful to understand our customers. 
The data for the communication can be used for brand sentiment, traffic analysis, shopping behavior,
strategic services, retail rewards etc. 

\section{Unleashes Big Data’s Power with HP Analytics Solution}
Jabar Liao: Regional Solution Manager, Hewlett-Packard
\subsection{Synopsis}
The speaker introduced HP Vertica and Autonomy solutions which helps to extract value from all forms of information in real time and at scale 
to improve efficiency, reduce risk, increase revenue opportunities, and lower costs. HP’s solution has been used to solve a 
wide range of information challenges, including talent management, fraud detection, insurance risk, social media analytics, 
traffic management, and health-care analysis. The Vertica Analytics platform is software dedicated to 
storage and analysis of very large amounts of structured data. 
The Autonomy solution indexes unstructured data within an enterprise and provide users a search interface.

\subsection{Relevant}
Enterprise Analytics softwares could be very useful for our organization to quickly get insights for business.  


\section{An Integrated Approach with Big Data Analytics}
Ron Dunn: Director of Customer Solutions, WhereScape Asia 

\subsection{Synopsis}
The speaker introduced a new approach of building data warehouse which is more adaptable to users requirements. 
The difficulty in developing traditional data warehouse projects including 
inaccurate or outdated business requirements, poor development productivity, cost of resources,
slow development cycles, unacceptable data quality, dismal documentation.
WhereScape sells data warehouse automation softwares that designs, builds and operates data warehouses 
using metadata to drive agile deliver with consistent quality and full documentation which saves time and money for their customers
and delivers value, faster, to decision makers.

The software runs on SQL Server, Teradata, oracle, IBM, Pivotal and used by 
Disney, Nike, GE Aviation, Telstra, Air Newzealand, Tesco, Volvo, Barclays.

\subsection{Relevant}
Business requirements can be changed across the time also for many projects, it is difficult to imagine the complete picture of the 
final system before seeing intermediate results. Having agile development systems could be useful for fast and flexible development. 





\section{Challenges and Opportunities of Implementing Big Data Technologies in Wind Industry}
Vinay Gupta: Head – Business Analytics and Business Excellence, Wind World India 
\subsection{Synopsis}
The growth of smart sensors and the BIG DATA they produce—along with new technologies that know how to crunch that information and produce meaningful results.
Developments have been made for: (i) power forecasting, and (ii) preventive maintenance. 
In power forecasting, it is used for planing the load distribution and to alter scheduled power. Techniques used for prediction includes, 
Double/Triple Exponential Smoothing, ARIMA/ARMAX Modeling, and Neural Networks. Whereas for preventive maintenance, they claimed 
to extend the lifespan of the average wind turbine by three years, increasing total average lifespan to 23-25 years.
Such an increase would result in a 17\% reduction in costs per year per wind turbine. The system uses complex knowledge base system (KBS).  

\subsection{Relevant}
Machine data from our aircrafts can be collected to predict machine problems before occurred. This could help reducing maintenance cost. 

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